1. Technical Field
The present invention relates to medical image processing, and more particularly, to a system and method for validating an image segmentation algorithm initialized by a single-click point.
2. Discussion of the Related Art
Image segmentation is the partition of an image into a set of nonoverlapping regions whose union is the entire image. The goal of image segmentation is typically to locate certain objects of interest which may be depicted in the image. This is accomplished by decomposing the image into meaningful parts which are uniform with respect to certain characteristics, such as gray level or texture.
Due to its ability to locate objects of interest, image segmentation has found increasing use in the area of medical image analysis. In particular, since computer-based medical image segmentation can provide fast, objective and consistent measurements for diagnosis and detection of certain diseases, it is in high demand by physicians and other medical practitioners alike.
Currently, there are two main types of computer-based medical image segmentation algorithms. First, there are fully-automatic segmentation algorithms which use feature extraction and prior knowledge to automatically delineate items of interest, and second there are semi-automatic segmentation algorithms which combine a physician's input with a segmentation algorithm. Since many physicians prefer an algorithm with minimal but some user interaction, semi-automatic segmentation algorithms initialized by a single-click point within a region of interest chosen by the physician are being increasingly used.
Due to the randomness of the physician's initial click points, consistency results between different initial points have become an important criterion in evaluating semi-automatic segmentation algorithms. One method for testing consistency involves initializing a semi-automatic segmentation algorithm at a limited number of randomly chosen points and comparing the segmentation results with a baseline measurement. Although this method is easy to perform, only a limited number of points are tested for consistency, thus large regions of interest containing hundreds of points may not be accurately tested. As such, a need exists for a technique of reliably testing consistency between different initial points to evaluate a segmentation algorithm initialized by a single-click point.